{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [],
   "source": [
    "# This is a hidden cell which will be executed but will not show up in Sphinx docs.\n",
    "# To hide a cell, in Jupyter go to Menu->View->Cell Toolbar->Edit Metadata\n",
    "# and enter in {\"nbsphinx\": \"hidden\"}\n",
    "\n",
    "# Set figure size and font size\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = [8, 4]\n",
    "plt.rcParams['font.size'] = 12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Understanding references\n",
    "\n",
    "In this tutorial we'll investigate what \"references\" are.  The GDSII specification allows the use of references, and similarly PHIDL uses them (with the `add_ref()` function).  So what is a reference? Simply put:  **A reference does not contain any geometry. It only *points* to an existing geometry**.  That still might not be clear, so let's use an example:\n",
    "\n",
    "Say Alice has a ridiculously large polygon with 100 billion vertices in it that we'll call BigPolygon.  It's huge, but she needs to use it in her design 250 times.  Well, a single copy of BigPolygon takes up 100GB of memory just by itself, so she doesn't want to make 250 copies of it. Since Alice is clever, she instead *references* the polygon 250 times.  Each reference only uses a few bytes of memory -- it only needs to know the memory address of BigPolygon and a few other things. In this way, she can keep one copy of BigPolygon and use it again and again wherever she needs to.\n",
    "\n",
    "If that's still not clear, let's use the following examples.\n",
    "\n",
    "## Using references\n",
    "\n",
    "Let's start by making a blank geometry (`Device`) then adding a single polygon to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import phidl.geometry as pg\n",
    "from phidl import Device\n",
    "from phidl import quickplot as qp\n",
    "\n",
    "\n",
    "# Create a blank Device\n",
    "P = Device()\n",
    "\n",
    "# Add a polygon\n",
    "xpts = [0,0,5,6,9,12]\n",
    "ypts = [0,1,1,2,2,0]\n",
    "P.add_polygon([xpts,ypts])\n",
    "\n",
    "# Quickplot the Device with the polygon in it\n",
    "qp(P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, pretend we're in the same position as Alice: We want to reuse this polygon repeatedly but do not want to make multiple copies of it.  To do so, we need to make a second blank `Device`, this time called `D`.  In this new Device we'll *reference* our Device `P` which contains our polygon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D = Device()             # Create a new blank Device\n",
    "poly_ref = D.add_ref(P)  # Reference the Device \"P\" that has the polygon in it\n",
    "\n",
    "qp(D) # Quickplot the reference-containing device \"D\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OK, well that seemed to work, but it also seems thoroughly useless!  It looks like we just made a copy of our polygon -- but remember, we didn't actually make a second polygon, we just made a reference (aka pointer) to the original polygon.  Let's continue with the example by adding two more references to `D`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "poly_ref2 = D.add_ref(P)  # Reference the Device \"P\" that has the polygon in it\n",
    "poly_ref3 = D.add_ref(P)  # Reference the Device \"P\" that has the polygon in it\n",
    "\n",
    "qp(D) # Quickplot the reference-containing device \"D\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have 3x polygons all on top of each other.  Again, this would appear useless, except that we can manipulate each reference indepedently. Notice that when we called `D.add_ref(P)` above, we saved the result to a new variable each time (`poly_ref`, `poly_ref2`, and `poly_ref3`)?  We can use those variables to reposition the references.  Let's try:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "poly_ref2.rotate(15) # Rotate the 2nd reference we made 15 degrees\n",
    "poly_ref3.rotate(30) # Rotate the 3rd reference we made 30 degrees\n",
    "\n",
    "qp(D) # Quickplot the reference-containing device \"D\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we're getting somewhere!  We've only had to make the polygon once, but we're able to reuse it as many times as we want.\n",
    "\n",
    "## Modifying the referenced geometry\n",
    "\n",
    "Now, a question naturally follows this:  What happens when you change the original geometry that the reference points to?  In our case, our references in `D` all point to the Device `P` that with the original polygon.  Let's try adding a second polygon to `P`.\n",
    "\n",
    "First we add the second polygon and make sure `P` looks like we expect:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add a 2nd polygon to \"P\"\n",
    "xpts = [14,14,16,16]\n",
    "ypts = [0,2,2,0]\n",
    "P.add_polygon([xpts,ypts], layer = 1)\n",
    "\n",
    "qp(P) # Quickplot the \"P\" with its 2 polygons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That looks good.  Now let's find out what happened to `D` that contains the three references.  Keep in mind that we have not modified `D` or executed any functions/operations on `D` -- all we have done is modify `P`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+oZT64OO/d/uoXSGCwsDAAI9tfJwPWvaSe2EZ8ysrde9VapqGIcKIIcIIZ/E7gcftwfVxkH/SKx90DDEx3o3L6sIz4AKnF6/D+3Gv/FiYf9IrL8krwmwdISYmhpjImGO316NjSYiJ57KLLyUuLs73/9Mz2Pj4OIcOHWL/viY+2NFAf6+d8LByoo0VmMe30d7eTkTE2d2BEZM36TDWNC0UqAVe1DStGYgAXgD+j1LKftznbgduB8jJyaGnp2eyhw5KFotFzp2fmUymKWvb5XKxa89uPji4k+iyRFYvu4iQ0FCwTNkh/SwSjBz7cwbZqZTCOBrCaOg4Hqcbt8uNqXOQtuZ2KnNnMTQ0hM1mm6qiZwSPx8PAwAAdHV0cOdRFT4+JsJAMwrQc8tLXMSs/GY1jv/B1D8zm4MF6iosLda46ePmiZ5wOGIDrgOWAC/gL8FPgXz75kFJqPbAeoLa2VmVlZfng0MEnPj4eOXf+5+tzrpRix44dPLjpETz5BkqurSIyLopxPIDHp8earjTNiDshlDHTOM1b6og1Gbnjxm8wf/583e8aBCKlFL29vdTXN7Dzg0b2f9QMnnSMWgWJcWtIii8mVDMA4LId+/OJcXM5uz54jYULa+T6ohNfhPEnvd/fKqV6ATRN+398LoyFEMe0tLTwwIaHaHN2U3RdFUm5KXqXFJDcLjdNW/Yxvt/MzZfewEUXXITBYNC7rIAyMjJCU1MTe3Y3sOuDRmyjRsK1CuKizqEs8+sYDdGn1U5SQin19ffjcrmmuGLxRSYdxkops6ZpXYDyQT1CzFhms5knN/2ZN+veJfO8ImrmrZAe3gkopej8sAVDvYvazEq+9OsbSUhI0LusgOBwODh8+DAHDjTxwXsNdB21EBFaTqSxgoykK4hOPbtf7MJCjRhCCujt7SU/P9/HVYvT4asHuB4BvqNp2maO3ab+HvCyj9oWYlqbmJjg1c2v8dSWTUQvSKHm7pWEhUsP70SGOwdpfa2ekqh8rr/8eubNm6d3Sbryer20tbVRV9fIzvcbaWo4iiGkAAMVpCTdytziPEI038wFN1BBe1sXS5b4pDlxhnwVxr8EUoDDgAN4Gvi1j9oWYlpSSrFnzx4e2PgwY6luyr+5iOjEGL3LCkjjljGat9Zh7FF8//q7WLx4Mb29vXqX5XdKKQYGBqivb2D3zkY+3HsYrysZAxUkxl1CVV4JYWHhU3LslKQKDh96YUraFqfmkzBWSrmAuz7+I0TQO3r0KA9ueJhGczMFl1VSWpiud0kByeNy0/JuI9bdA6w7/xou/85lhIdPTdgEqtHRUZqamti759i4r3lYER5aSWxkLUWpXyYi3D9TuOJj8xgeGmdkZESGBXQgy2EK4UOjo6NsfO5pNu9+nbSVBdTUrpQlJU9AKUV3fSfd246wrGwxt/z8X0hJCZ4H2Y4cOcLePft5f0cjHW3DRISWERFWQUrSReQVp+vyLEGIFoIhJIumpiaWyL1qv5MwFsIH3G43r//1dR5/6c8YK+OYf/cKjJHB1cM7XSM9JlpeqyNHS+Pf7rqXsrIyvUvyu1/+/I84zEvITL2JuUUFhISE6l0SAMawHPbubpQw1oGEsRCToJTiwIEDPPDnhzDFjFHy1XnEpsbrXVZActjsNL9eD61OvnXNraxYviJo7xpUVZXQsr+QpIRivUv5jLiYHHbt3Mpddyt50t/PJIyFOEu9vb088tRjfNh1gPyLZjF/VnA/+ftFPG4PbR8cwryjhytXXMbV37yKqKgovcvS1aIllXz0QQPZLNS7lM+IMMYxajXQ29sri3/4mYSxEGdofHyc5158nr+88wrJy7JZeOVqQkKDs4d3Kn2Huujccoia3Ln8/Gc/JCMjQ++SAkJlZQUT3s0oFXg90HCtgoaGRgljP5MwFuI0eb1e3nr7LR557jG0kkjm3LWMiBjZXehERgcsNG+pI3kslnu+9mOqq6v1LimgpKWlkZAEY+MDxEQH1pP2cVEVfPD+Ds4/f43epQQVCWMhTkNTUxPrn3yIHgYpvqmahMwkvUsKSBN2J81/bWCi0cpXr7iJNavXEBYml5nP0zSNxUsreX9bQ8CFcUpSOfs/egy32y3/dn4kZ1qIkxgaGuKl115m28HtZF9QyoKq5QF3WzEQeL1eOnY3M/h2J2sXnc/1/7aO2NhYvcsKaAtqKnjztd3Aar1L+QyjIRrc6bS1tVFaWqp3OUFDwliIE3A4HLz06ks888YLlC2rovbuVYQa5MflRAZb+2h7rYHKpFJ+/M+/ITc3V++SpoXy8nIcng14lddnS1r6ijGkggMHGiSM/UiuLkIcRynFBx98wINPP4IrR6PqjqWkqgRshgm9Sws4Y6ZRmrfWET1k5Ec3/iMLFiyQuwZnIDY2lvzCZEYsbQE3xSkxroJd7/+Fa6+9Uu9SgoaEsRAfa21t5YEND9FiP0rxtVUk5aYee2NE37oCjdvpovntRsY+GuLmS25g7YVrZWvDs3TOskpefKox4MI4Kb6Yg4e6GR8fD/ppaP4iYSyC3sjICE9u+jN/PfgOGasLqZ2/Unp4J6CU4ui+Nnr/2sp5s5fzpV/dQ2Jiot5lTWuz51Tw7FOvAJfpXcpnhIYaMIYWc/jw4aDfOctfJIxF0HK5XGzeupkNr24ker5sbXgypqNDtL1WT2FEDv/xvV9RVFSkd0kzQklJCR51FJfbgSEsQu9yPsMYUsG+jxoljP1EwlgEHaUUH374IeufepixlAnKb1tIdJI8+Xsidss4R7YdxNCl+O66O1i6dKncNfAho9FI9ZxCBloPk5E6R+9yPiM1sYIPdqzn1q/pXUlwkDAWQeXo0aM8/OSj1JsOk39xBSXFsiLUiXhcblrea8Kys5/r1lzFFd++nIiIwOq5zRSLlpSz4UBjwIVxXEwObS12hoeHSU5O1rucGU/CWASF0dFRnn5+E6/t3EbaynxqrpetDU9EKUVPfSfdrzeztGQhX/nFT4Jqa0M9VFdXMqEe0buMv6NpGuFh5TQ1NbFs2TK9y5nxJIzFjOd0Ovnez36Atyyc+d+RrQ2/yEjvsa0NM70p/PKOn1FeXq53SUEhNzcXY6QVu3OEyPAEvcv5jGhjBbt3NUgY+4GEsZjxjhw5giPBw7xL5+tdSkByjjk48nodqtnO7Vd/hVUrV8ldAz8KCQmhZuEsGnc3kZsZWPsIpyRVsHvncwG5ocVMI2EsZrwD9QeJLIjTu4yA4/V4afvgEMPvdXPFuRdzzTeuITo6Wu+ygtLCRZXsfqcBCKwwjopIwjkeTVdXl6ysNsUkjMWMt7NuN6kXyYNax+s73E3n5kPMy67mnp9+n8zMTL1LCmqVlRU4PS8GZA/UoFVQX98oYTzFJIzFjGa1Wuka6mFRdqXepQSE0UELLVvqSRyN4qdf+T/MmTMn4C7+wSglJYWUdCOjY73ExQTWPsLxMRXs3LGdtWsv1LuUGU3CWMxojY2NROXHBf0YqMsxwZE363HWWbjl8i9xwZoLZHu8ALN0aSXbX20IuDBOSZzFwQMP43K5ZNnTKRTcVygx431Ut4/owuBdstHr9dK++wgf/vYtzomYy33/9jsuvuhiCeIANG9BBRPeRr3L+DuGsEhCVDYtLS16lzKjyU+kmLGUUuyq20Pul6v0LkUXg239tL/WQHlCMf/8T78hLy9P75LEScyaNQun5094vG5CQwLr0mzQjm2pKNPdpk5g/YsL4UN9fX3Y1DjRycG11OWY2Ubz1jqiBkL5Pzd8l9ra2tMaF1ZKYbFYiI+Pl3FkHURHR1NUko7Z1EpKYpne5XxGcnwFO3ds4vrr9a5k5pIwFjNWQ0MDkYVxQRMsbqeLlncbse0d4saL1nHJ9y7GaDSe9GusViuNjY18VLePXXV7MI+PkBqXwnmLVrF00RLy8vKC5vwFgqXLKnn+icaAC+OE+EIOtvQzNjYm09+miISxmLF21+0lvihV7zKmnFKKo/vb6H2jlVVVy7jpl/9KUlLSCT/rdDo5cuQIB+oPsrNuN11DPUTnxxFVkEDul6soT47F0mdm68H3eO5/XiIpLJ41S1azdNESsrOzJZinWHV1OU+rF4Ar9S7lM0JDwggPLaWxsZHa2lq9y5mRfBbGmqaVAgeBZ5RSX/ZVu0KcDY/Hw76m/VRfMLOX8TN3DdHyWj35hiz+/bu/oKSk5DPve71eOjs7OVhfx66De2hqa8KYEUVkYTwpF2awKKfy7540T8hMIiEzCXWBYqTHxGsH3+bp/3qetMhkzl+ymsULF5OVFVhP/M4UJSUleEN6mHCNYzRE6V0OHq8bs6UVk6WRcXsv7e1HJYyniC97xr8HdvuwPSHOWltbG1qCgfDombnTkGPUzuFtBwltd/Gddd9k2bJlaJqGUorBwUEaGxvZXbeXDxv24Y2GiII4khekseCa1ae9Z7OmaSRmJ5OYnYy6SGHuGubFg2+w4d83kRWbxpqPgzkjQxZU8ZWwsDDmziuh+9AhMtP8v3yrQmG1dTNoasTpaWTC20xxaQZXX1bB7Dlfobi42O81BQufhLGmaTcCI8AOoOQUHxdiytU11BFRMPMe3PK4PbTuaML8fi/Xrr6Sq+68Eo/Hw969e9nfcICdB3djcowQVRBPfHEK5SsWERk3+R6Wpmkk5aaQlJuCulhh6hzkuYNbeXzrU+QmZnPe4pUsXriYtLQ0H/xfBreFi8tp+LCRTPwTxnbnCEOmRmyORtLdA4yrUVZdUsm8BcuYNevrMkbsJ5pSanINaFocsAdYA3wDKDnRbWpN024HbgfIycmp2blz56SOG6zeeecdli9frncZAW/Ds3/GXWYgIePEY6dnImIsDEe02wdVnT2lFObuYYb39VCcWkh5cRnmETOHO5sZNA9iTI0mPC2S+MwkIuOi/Da2q5TCOmjB2jmMvdtGWmwKs8uqKS0pITZ2cr8MmUymLxz7nsmGh4d5eP1W8tO/NCXte7wuRm09jNm7cNNFmNFOcUkWJaW5JCTEyxDEFMrOzt6rlDrhfX5f9Ix/CTyklDp6sguAUmo9sB6gtrZWyT/42YmPlx+WU7Hb7eys203txedhM0z4pE1bgm/aORuWfjP1z++BLhfZGVls73yb9zp3EVkUT/L8dNJzywkNCwXAC4zh8mt9oYlRJJZFEe/1MtQ2wKa6Vxh71UxRRgFrFq9iYe3Csw7VYPxez8zMZGj4TxgnwomKTJ50e16vhxFrO0MjjbhUAx66qJ5TyOpVFVRVXUNubu6nzw309PQE5TkPBJMKY03T5gHng5/upwhxGg4fPkxEdgyhhuk7WcDpcDDQO8CBV3fTs6OdrMws8paXYChNZn5RJYaIk09Z0kNISAhpxRmkFWfg9XoZbO1jw8EXWP/CI5RlFXPekmPBnJAQWHv2BhpN06hdVM6BHU3kRZ75A4hKKWzj/QyZGnG4G3F4DpNfmMzlF1UyZ+5llJSUnHLKm/C/yV6tVgEFQOfHveIYIFTTtEql1IJJti3EWdlff4DIgni9yzgjbrcby8gIQ+ZhBoYG6TnYieXDfvIrCln3X7eSkDn5HpI/hYSEkF6SRXpJFh63h8GWXh4/8Cz3PfsQlfmzOG/xKmpqaoiLk60tT2Thokref7MeOL0wdjitDJmbGLU3MuFtJCEJll5QyYKahZSX3zLpIQMx9SYbxuuBp477+w85Fs53TrJdIc7azro9pF6Wo3cZJ6W8Xqyjo5jMJgZMg1jHrIRFGxk32RjZ2UdGagZr772Y+Izpv652aFgoGbNyyJiVg8ftYeBID4/s3cjvn15PVWEF5y1eyYIFCyQwjlNRUYHT8+wXbqno9kxgGjmC2dqIi0ZCDMMsqClj0ZJKKivXkpaWJnPCp5lJhbFSahwY/+TvmqbZAIdSanCyhQlxNsxmM30j/eRnzdG7lL8zPj6G2WRmwDyIacQM4SGExRqISI8idiKBnjdaCRn2suqqNWRVzsyVr0LDQsmsyCWzIhePy03foW4e2vUkv/3zfcwpqWL1x8Ec7E/wJiYmkpEVjdXWRXxsLl7lxTLayZCpkQnVgFt1UFGVx4VLypk9+2YKCgqCfmey6c6ng2pKqXt92Z4QZ6qxsZHogsBYW3liYoIRs5lB0xCD5iHcmqsOaHwAACAASURBVIewWCPG+AiScjMICQvF43TT+3Yrtv3DzF21gNJbqz59GGumCzWEkV2dT3Z1Pu4JN32Hurh/x+M4Nvye+WVzWTpvMQkJCURF6b/4hR4WL63gmSdeISZGw+FpIic3nrXXVjJ33oWUlpYSETEz59AHq+n7hIsQJ7C37iNiivSZDuPxeLBYRhg2mRgwDzLuHCcsJhxDnJHYsiTCjnvoSinFwIddDL/VSWF5Ced9f41P5gNPV2HGMHJmF5AzuwC300VvUxdbGrbzh6cfYGHFAlYtWcHcuXODKoBWrV6K0/kWc+fNorz8BnnwbYaTMBYzhlKKPXV7Kfz6PH8dEOvoKOaPx31HbBZCowyExRiJzI0mJjoJTtBDH+0007ulmfjwOC689XKSclP8U+80ERZuIHduITH5RuIvyKar8Si/feNBJh4ZY2F1DasWr2DOnDmEh4frXeqUKigo4I5vFehdhvATCWMxY3R3d+MwuIhOjJnyYzUeaqRnsA8MEBZrJDwtktSibLTQLx63c1oc9LzejLfbweKLl5I7ryggbqcHMkOEgbz5ReTNL2LC7qS94Sj/s2U9Ew+NsXTOIlYsXs7s2bNlqo6Y9iSMxYzR0NBAZMHUT5UZ6O+n29JHUlXaac1l9rg89L/XjmVPP1XnzKXixtmnvT60+BtjZDgFNSVQU8LEuJMj9Z3sfuUPeB90snTuYlYsPpfq6moMBjm3YvqRMBYzgsvl4t29O0iYM7W3fL0eD42th4grSDxlECulMNX3MfBGO7mFeaz4h3V+6bUHA2NUOIULS2FhKQ6bnab6Tnb95Xd4H5zg3HlLWb74XCorKwkLk0ucmB7kO1VMa0opPvroIx546iFGkyaoKls4pcfr6OzEG6URHht50s+N9Vrp2XyEKG8Ea266mNTC9CmtK5hFxERStHgWLJ6FY9TOwbp23nt2D9zvZsWCZZy7eBnl5eUSzCKgyXenmLa6urp4+MlHOTjYRMHaCopKMqf0eA6Hg9buNhIqv3hnIpfNSc+bLUw021hw4SIKFpbK/E8/ioiNpHhpOSwFu2WcD+uO8NZTHxA64mVl7XLOXbyMWbNmyb+JCDgSxmLasdlsPP38Jl79YCupK/KpXbfKLxfXIy1HMKRGEmb8+zFJr9tL/84OzO/3UFFbReUP52GMnNlP+wa6yPgoSpdVwjIYH7Gx+2ATbzzxLsbREFYtXM45C5dSVlYmwSwCgoSxmDY8Hg9vvPlXHvvLBgzlMcy/ewXGKP8EnsVioc8yQGr1Z3e0UUoxcniQ/m2tZGRksuzb1xKbOr3WxQ4GUQkxlC6vhOUwZhrlg4N1bP3TdiLGw1i9aAXnLDqHkpISebpd6EbCWEwL9fX13L/hQQYjLJR8ZQ5xaX5cAEEpGpubiM6JRzuuF2UftNG9pRmjTWPl1WvImBXY62GLY6KTYildWQUrwTZk5e39H7LxP54nIyaVO750G4sXLda7RBGEJIxFQOvv7+fRpx5jd8c+8i4sY355td97L+YRM2PYSUnMAMBtd9GzvRV7g5n5axZSvLSckJPMLxaBRSmFbcjKQHMvttYR7J0WZmUWs6h6Ifl5+XqXJ4KUhLEISHa7nRde+gvPbX+RxKWZ1F62Spc1m91uN939vcQVJqIUDO7pZOjtLkpnl1H9gwuIiDn5U9UiMDhsdgZb+rC0DjHeaiEuNIaFs2tZcP48ysvLZStHoTsJYxFQvF4v77z7Dg8/+xiq0Micu5YRcYppRFOpraMNQ5SGvX+Mtq0HSIpN5OLbryQhU5/1r8XpcU+4Ge4YYLi5H3u7Fc3qZX75XK6as5rKGytJT0+X8WERUCSMRcA4cuQI6zc8SKenj+IbqknMTta1Hvv4OEcOHybXloqppYNzLl1OdnW+XMQDkNfrxdJjYuBIL/aOUZw9Nmbll3LV7POpvqCagoICQkODYzcsMT1JGAvdDQ8Ps2HTk7zd+D5Z55dQM3uF7oHncrj46+Nb6Ks7yjk3zKfyqgWntfSl8J8x0ygDzb2MtpoZ77CQlZjByupa5l49h7KysqDa4UlMf3J1EbpxOp28svlVNm59ltjaVGruXkWYUd9vSaUUnR+2cOSlg4z2D3LDr79GRkgyNsOErnUJmBh3MtDax0jzIPZ2K1HecGqra6hZcSXl5eUkJibqXaIQZ03CWPidUopdu3bxwNMP48hQVN6xmKj4aL3LYrhzkNbX6ikMzyEjIoXq7y0kJikWRvSuLDh5PV4GWvoYbunD3mbFa3IxZ9ZsLqu+msrrKsnKytL9DooQviJhLPyqo6ODBzY8xGFrG4VXVJJSoP+azXbLOEe2HsTYrfjH6+/EMmrhsV2bZN6wnymlsPSZj437tltJdcVjNBi4bPYqqldWU1RUJOtLixlLvrOFX1gsFp56biPbPtxO+qp8amtW6d6r8bjctLzbiHX3ANetuZorvnM5ExMTfOsnd1PylXm61hYsxi1jx8Z9W4YZb7eSGpPMObNrmXfZXBISEigsLNS7RCH8QsJYTCm3283W17fyxEt/JmJOIgvuXokhQt/9ZpVSdNd30r3tCMvKFnPLz/+FlJRjWy8+sXEDxso4YtNkScup4HJMMNjaj7llAHubFYMzlNrqBdQsuZjKr1eSnPy3J+h7enp0rFQI/5IwFlNCKcW+fft44KmHscTbKf16DTEp+i+sMNJjomVzPdmk8us772HWrFmfvnf06FE273qdeXcv17HCmcXr8TLcOchwaz/2VguuQQezS6u4sPoyqq6oIjc3V/c7JEIEAglj4XM9PT08vOER9vc3kH9xBYUlWaf+oinmsNlpfr0O1eLkW9d+lRXLV3xmtx6lFA9ueJjUFXmy29IkKKUYHbTQf6QHe7uV8Q4LhZn5XFR9DrNvnk1JSQkGg753RoQIRBLGwmfGxsZ45oVnePn9LSQvy6H2utW6b0/ncXto++AQph09XLn8Uq755tVERUX93ef27t1Lg+kItTes8n+R05zdOn5sqcmWIewdVhLD41lUXcu8C+dSXl5OTEyM3iUKEfAkjMWkeTwe3nxrO3964QlCy6KY9+3lftva8GT6DnXRseUQC3LmcO9Pf0BmZuYJP+dyuXhg48MUXlKp+y8P04Hb6WKovZ/h5gEc7VZCx2B+5Txqa86n8pZKUlNT5dazEGdIwlhMSmNjI/c/8QB9BjMlX64mPl3/hRdGBywc2VxH8lgM//rVf2b27NknDYfNWzdjS3FRUpThxyqnD6/Xi7lrmKGWPuxtFib6xqkoKmdV9VqqL64iPz9ffokRYpIkjMVZGRgY4LGNj/NBy15yL5rFgooq3XtDE3YnzW82MNFg5dYrbmLN6jVfOC91aGiIhoYG9tZ/xDv7dzDnjnP8XG3gUkoxNjxK/5EextpGGO+0kpOSxXnVi5izbjalpaWEh+t/50OImUTCWJwRh8PBX15+kWf/+gIJSzOp/c5qXbY2PJ7X66VjdzODb3eydtH5XP9v64iNjf3MZ8bHx2lqamJf/X52HdzD0LiJqMJ44gqTmHfXciLj/34cOZh8ZovBNiuxIVEsqq5l/nnzqKiokC0GhZhikw5jTdPCgT8A5wNJQDPwE6XUa5NtWwQOpRTvvfceD256BG+Bkeo7zyEyTv8AG2zto+21BiqTSvnxP/+G3Nxc4Nj85paWFuoa6th5cA8t3W1E5sYSVRhP2rVFFKUv0L0nryePy81QxwBDR/pwto+iLB7mlc/hytmrqLyhkoyMjKA+P0L4my96xmHAUWAl0AlcAjytadpspVS7D9oXOmtpaeGBDQ/R5uymaF0VSbkpepfEmNnGkS0HiRky8E/X/wM1NTX09PSwdetWdtXt4eDhekKSDUQWxpGyPIOFeWt078HrSSnFSPcwgy39jLeN4OwZoyyv5NgWg+dXU1hYKFsMCqGjSYexUmoMuPe4l17WNK0NqAHaJ9u+0I/JZGLDpid5q34HmWuKqJmr/9aGbqeL5rcbGPtomCuWX0LO0hw++GgXv3v8jzgMLiIL4kiYlcKcS84NyPnCHrfbb8caM9sYaO7F1j7CWNsIGfFpLK5cwOy11X+3xeDEhG92pYqIiND9e0SI6UhTSvm2QU1LBzqAeUqppuNevx24HSAnJ6dm586dPj1usHjnnXdYvnxqV4hyu918+NFHvLtvBxHFsWSU5+i+l69SioHWXvr3dJIQFkdoeBhjrnHC06KISI8hPjORiOjIKTl2xFgYjujJhahSis6uTsyjI0xVVnldXhzmcZxDdib6x1EOD1HhkURGRBEZE+mXTRZyU3O45Py1xMdPfjlRk8lEUlKSD6qa2f7wu0ewWJw+aSs1LYHBgclvUxYfH85dd3/NBxXNLNnZ2XuVUrUnes+nP52aphmADcCfjg9iAKXUemA9QG1trcrK0n9VpukoPj6eqTp3Sin27NnDAxsfZjzNQ8mV1UQnxmDHC/h/P1+lFKOjVtob2qh/YQ+OLhulNeW4F4STWpJIZlb+p70wN2CbwhptCWfftlKKuoY6BtwmkqvT0Hw0Dcjr9mLrGsHaMoy93Yp72EFafibZpbmkX1JNfEaiX3upSima3z/Ez3//a7525S1csOaCSU95kuvEqe3f10lt2f0+aSsutAdlmPw537PvDvm3O0M+C2NN00KAxzl21b7bV+0K/+jo6OChJx+haaSFgssqKS3UZ2vD8fFxzGYzg6Yh+rp7GfywC1eXnXkX1TLn4lrCjNNrKcVPg3jCRHLx5IJYKYW934albZjxVguOrlES05LIK8sj/bJakvNTdR0X1zSNonPKsc3K5uEXnuTd3Tv4zm3fJi0tTbeahJgufBLG2rFfvx8C0oFLlFIuX7Qrpp7VamXjc0+zZc8bpK8qoKZmpV8XcHBNTGAeGWHYNMyAeRCXchMSGYrl8BDjB83MWTaXyu/P032np7PhiyB2WhxYW4cZazMz3m4lMjySnNJcMpaVk1aUERArnX1eTHIsNV9fQdv7h/juL77vs16yEDOZr3rGfwQqgPOVUnYftSmmkNvtZtsb23j8pT8TXh3Pgu+sxBBhnPLjej0eLBYLw2YTA6ZBxhxjhMUaCYsNJ7okgdE2M/2b28nOzmL+P15ITHLsqRsNQGcbxB6nG2ubidFWE/Z2K4x7ySrNoWhWNemXZRGdND3Oh/SShTgzvphnnA/cATiBvuPGqO5QSm2YbPvCt5RSHDhwgAf+/BCmmDFKbp1PbOoU7t2rFKM2GyaziUHTECOjZkKiDITFGInIjSQtOhE0jfH+UTqeaSDcHsbqdReQHgA7PZ2tMwlir8fLWLcFa+sw9jYrEwN2UvPSKS0tIv2cTOKzkqZ1j1J6yUKcHl9MbeoAZC7DNNDb28vDf/4T+7rryFs7i/ll86bkOA67/di4r3mIIfMwygBhsUbCUyJIKcxGC/3bhdg1PkHvmy04DlmZf8FCihbPmtYX6lMFsVIKx9DYp+O+9g4r8SkJ5JTmkbF2Psn5aYQZZ9bCeNJLFuLUZtZPvTihsbExnv3Ls7z03mvHtja8ahUhob4LPLfLdWzc1zzMoGkQp2eC0FgjxrgIEjLTCD1BuHg9Xgb3HGX43W7K5pcz+4cXB+T455n4oiB22ZxYWoextZqxt1sxhhjIKcujcmEpqTdmEBEzNVOyAo30koX4YhLGM5jX62X7W9t59PnHCSmNYu63lxMeHXHqLzyNdq1WCyaTiX7TIDa7jbAYI2GxRiKL44mLMHKyybQjzUP0bWshNTGVS751VUDs9DRZxwdxQm4SlpbhY+O+bVa8NjeZRdlUlVaQflEWMSlxQbswhvSShTgxCeMZqqmpifs3PEhvyBDFN1WTkDm5xRNsNtvHU44GMVnNhESEERpnICI7krToBAg5dbjYh8bo2dZMqFlx7qWryKrMnRGh5PF42PXW+3S2dBDqDKG/v5mU7DSKSvNIvz6bxJxk6f19jvSShfgsCeMZZmhoiMc2PsH7zbvJPr+EBVUVZxV4Tofj43HfYYbMQ3hDFKFxBsKTIknOzyTkDOazuh0u+t5pw7Z/mLmrayhdVjmt14n+dIvB5l5srSYa3jmIQzmZc3EtWbNySS1MJyx8+k3F8jfpJQvxNxLGM4TD4eDFV17imTdeIH5xOjXfXnlGS1i63W4sIyMMmYcZNA1hdzkIizVijAsnLiPlrBbbUF7F0L5uBrd3UlxZwpofnE9E7PQcH3WOORho6cPSOoi9zUo0kdRUzufIsJPCmlIW3rpiWv+Coacv6iULEUwkjKc5pRTvv/8+D256FFeORvW3lp7W3rzK68U6OorJbGJgeBDruJWwaCOhsQYiC2KIjUo+6bjvqVg7TPRuaSYhIoG1X7+cxBz9d3o6E59sMTjc3E+KJZbOtg7mzZrDFdUrqFxXSVpaGr+9/3cMJI6y8EYJ4sk6US/5pqtvlCUVRdCQMJ7GWltbeWDDQ7Taj1J0bRVJuakn/fz42Bhms5kB8yCmETNEhBAWYyAiI4rU2GyfrJnstNjp2daM6nGy5JJl5M4tnBbjwkopRnpMDDb3Md5uwdltozS3mCtmn0debR5z5879dKMFj8fD/973W3aNHGTujUskiH3o+F7yQ5se5YKl58lYsggKEsbTkNls5s/PPMVfD75DxupCauavPGHgTUxMYDabGTINMWgewq15jt16jo8gKTfjjMZ9T8Uz4aZvRwfWPf1UL5tH+U2zA36+7KdbDLaaGGu3kBGfxrnVNcy7ch5lZWVERh67pd7T0yNB7Eef9JLDcj08vFXGkkVwCOyrpfgMl8tFfWM9j770BNHzU6i5e+VnHhTyeDxYLCMMm0wMmAcZd44TFhOOIc5IbFkSYVOw3KVSClNdHwN/bSevKJ9V31tHVEKMz4/jCxN2J4MtfZhbB7G3jxLpMlBTtYCaZZdRcVvFKbfrkyD2r4jYSHniWgQNCeNpQCnF3r17eWDjwzhCJii/bSHRSbEopbBarZg/Xud5xGYh9OOlJiNzo4mJTprUuO+p2Hos9GxpJtobwZqbLiZVp52evojH7cHUOchQSx+O9lHcg05ml1WxtvoKqq6qIicn57RvoUsQ60OeuBbBQsI4wB09epQHNzxMg+kIhZdUEttpx2K30lzXytCICT5ZajItktSizy41OVVcNifdbzTjah2jdu1i8mtKAqK3opTC2j/CQHMv420W7EdHKcoq4OLqFcw+t5ri4mIMhjN/Ktzr9UoQ60zmJYuZTsI4QI2OjvL085t46b3XiFyQRMy8DBr6DxPaOYEtGgyx4YQXxBBqOBYMCrA7pnbDLK/by+CeLszv91BQXUzRzQsICzfQ29s7pcc9GeeoHVPHIKNtx5aajA2Npiy3lPl5C8idl/vpuG93dzfd3d1ndYxDLYcliAOA9JLFTCZhHGDcbjdvvPkGj734JJ0RAxgXxTKR7GTMCBGFsbgHLZCu4cKLyzt+bK+sKaaUwtZiZuiNDiLjosm+vIyQhEja7d3g5w0zPRNuxrqtjHWOMN5mxWt1kZCSRGJqEhnz84iIiWQYO8OqgV2dDT45ZnZchgRxAJFespiJJIwDSF1dHfdveJChKCulX5mHq/swntRQIhOiAfC43Xg0jfDYya8vfbocA2P0b2sDm5fKdQtJKPHvfGHlVdi6Ro7bYnCc1Nx0Sirmkn55FgnZU7/FYMyIEVvYxJQeQ5wZ6SWLmUbCOEDs2bOHXz34G4qvmc2CWXMASLWn0jHa/WkY+5Pb7mLwrU7GGkzkrSojrTbXpzs9fRGlFI7hMSytH28x2GklPimB7NJcMi6aR0pBesBPmRL+I71kMVPIVS1AVFRUEGeMISLub6tnJSUm0tLX5tc6lFdh+rAX0ztdpFZlU/adlRiifD8l6niuMSeWVhNjrSbG260YNQPZpbnHthi8IWPaLqEp/EN6yWImkDAOENHR0dx69S2sf+0xFnxtOZqmERsbBxMKr8tNyBmsM322bK1m+re1ExUbzeyvLiUqPXZKjuNxeRjtMGNrHf503DezKJvK0grSLwzuLQbF2ZNespjOJIwDyKqVq3jpr6/SU99JdnU+mqaRnJDMuNVOdPLUBCOA02Sn//U2PIMTFF9UQWJ5uk/DUHkVY73Wj8d9LTh6x0jJSqWgNJeM67JJzE2RC6bwCekli+lKwjiAhISEcMfNt/Gz+39JxqxsQg1hpCalcNjUOiVh7HG6GXz3KKP7BslZVkLm9fmEGHzzxLDDNH5s3LdtBHuHlZjYGLLL8shcXU1KYQaGCNliUEwd6SWL6UbCOMCUl5eztGQhje81UbaqmsTERDwdLlDKZ8dQSjGyv5+h7UdJLkln/l0rMMZN7glt9/gEljYTtlYz9nYLoe4QsktzmTV3PmnXZJ7WTlJC+JL0ksV0ImEcgL5yw5e561//Afv8IqLiozBoYbidLrSwyf9WP3bUysDWVoxhRqpuWkRMdvxZteN1eRg9OsJoqwl7uwW3aYL0gkzKS0tJPy+LuLQEGfcVAUF6yWI6kDAOQCkpKVy35ipe2vY6c65bTGpiCsOWUaKTz34DBpfVSf/r7Ti7bBScX07KnKwzCkulFON9o8fGfdst2LtsJKUnk1eaR8YVtSTlpcqiGCJgSS9ZBDoJ4wB1xaWXs/nH2zAdHSQlKYX+niE4izD2ujwMvd/FyO5+shcWkHV1DaGnOU/XabFjaTk27jvebiUqKoqcslwyllWQWpyBMTL8jOsRQk/SSxaBSsI4QEVERHDbulv5n5fvY86tS3EfmkCdwbixUgprwxCDf+0gPjuZ+d9aTnjCyefruh0urO0fj/u2WdCckFWSQ0nlbNKuyCI6MTC3RhTiTEgvWQQiCeMAtnTpUl564xX6GrqJjohmYvz0FqK299ro39pKiCuE8msWEFdw4n16vW4vtu5jS0062qxMDDpIy8+gtKSIjHOzic9MlHFfMWNJL1kEEgnjAKZpGt+8+Rv803//lORLcuixDnGyG8Mu2wSD2zsYb7aQv3oWaQty0EL+FqZKKeyDNqytpmNbDHZaSUhNJKc0j4xLFpCSn0aoHxYXESJQSC9ZBAq58ga4oqIizpu9nO2Ne/DkTAB//5CU1+1leHcP5h09ZMzLpfzueYRFHpvHO2F1YG0zYWs7dus53BBBTlkulYvLSLspg/Bo/206IUSgkl6y0JuE8TRw07ovsf3H72A32IlUf1v8QynF6BETg6+3E5Mcx9zblmGMC8fabsbWasLebsVrc5NVnE11aRXpazOJTo6VW89CnID0koWefBLGmqYlAQ8BFwJDwI+VUk/6om0BCQkJ3HLZl/j58/9JfMWxHZwcg+P0b2tDWdxkLSgEr6L75UNM9I+TkpNOcWk+6Yuz/bLFoBAzifSShR581TP+PTABpAPzgFc0TduvlKr3UftBb+2Fa/nfh36Ho9/GwMvdmHf2EhMXizHEgLdpjJzSXDIunEtKfhph4bLUpBCTIb1k4W+TDmNN06KBa4FqpZQNeFfTtBeBW4AfTbZ9cYzBYODWa7/Cfz/4OwaHu8jKySYpJJn45HgM4UZUp5PezhZ6adG71BknOymLblOP3mUEnUA57yEKdrfv5Uf3/Jj/+vV/kpR04tkJQkyGL3rGZYBHKXX4uNf2AyuP/5CmabcDtwOkpaWxefNmHxw6uCQlJXH+klXMnTtXxn39yG63U1swV+8ygk6gnXdN09i5c2fA/eylpYfS0P1Nn7SVaI/BbLJNup20dINc48+QL8I4BrB87jUL8JlthpRS64H1ALW1tWrt2rU+OHTw0TQNOXf+1dPTQ1ZWlt5lBB0576fHl9cDOef68cUTCTYg7nOvxQGjPmhbCCGEmPF8EcaHgTBN00qPe20uIA9vCSGEEKdh0mGslBoDngN+oWlatKZpy4Argccn27YQQggRDHw1ce4uIBIYAP4M3CnTmoQQQojT45N5xkopE3CVL9oSQgghgo0sKSOEEELoTMJYCCGE0JmEsRBCCKEzCWMhhBBCZxLGQgghhM4kjIUQQgidSRgLIYQQOpMwFkIIIXQmYSyEEELoTMJYCCGE0JmEsRBCCKEzTSnl/4Nq2iDQ4fcDzwwpwJDeRQQZOef6kPPuf3LOp1a+Uir1RG/oEsbi7GmatkcpVat3HcFEzrk+5Lz7n5xz/chtaiGEEEJnEsZCCCGEziSMp5/1ehcQhOSc60POu//JOdeJjBkLIYQQOpOesRBCCKEzCWMhhBBCZxLGQgghhM4kjKcJTdOSNE17XtO0MU3TOjRNu0nvmoKBpmnbNU1zaJpm+/jPIb1rmkk0Tbtb07Q9mqY5NU179HPvrdE0rUnTtHFN097UNC1fpzJnlC8655qmFWiapo77XrdpmvYzHUsNKmF6FyBO2++BCSAdmAe8omnafqVUvb5lBYW7lVIP6l3EDNUD/Aq4CIj85EVN01KA54DbgJeAXwIbgSU61DjTnPCcHydBKeX2b0lCesbTgKZp0cC1wM+UUjal1LvAi8At+lYmxOQopZ5TSr0ADH/urWuAeqXUJqWUA7gXmKtpWrm/a5xpTnLOhY4kjKeHMsCjlDp83Gv7gSqd6gk2/5+maUOapr2nadoqvYsJElUc+x7//9u7gxYbwzCM4//LjJrCpCwtlEk2ykKahbKkbCgb4gsQaxaThfIFfAFJsmNhw87GQlmJkrJQNozSNKQpdVu870gnduZ9Ouf9/1an52zunnPX1Tn387wHgKr6DrzHnh/ChyQfk9zpf6HQAAzj6bATWJtYWwN2NahlbK4B+4G9dA9EeJxkqW1Jo2DPD+8LcBTYBxyh2+v7TSsaEcN4OnwDFifWFoH1BrWMSlW9qKr1qtqoqrvAc+BU67pGwJ4fWD8Ce1lVP6vqE3AFOJFk8nPQFjCMp8M7YD7JgT/WDgMe3hpeAWldxAi8oetx4Pe5iSXs+SFtPp7Rfh+AYTwF+nnZQ+Bmkh1JjgGngXttK5ttULNAKAAAAMhJREFUSXYnOZlkIcl8kgvAceBp69pmRb+vC8AcMLe518Aj4FCSs/37N4BXVfW2Zb2z4F97nmQ5ycEk25LsAW4Dz6pqclygLWAYT4/LdNcQPgMPgEtea9py2+mugKzSzdOuAmeqyrvG/88K8AO4DlzsX69U1SrdDYJbwFdgGTjXqsgZ89c9pzsb8YRuFPAa2ADON6pxdPyjCEmSGvObsSRJjRnGkiQ1ZhhLktSYYSxJUmOGsSRJjRnGkiQ1ZhhLktSYYSxJUmO/AAR/30ZkYZacAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "qp(D)  # Quickplot the reference-containing device \"D\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have our answer!  **When we modify the original geometry, all of the references automatically reflect the modifications.**  This is very powerful, because we can use this to make very complicated designs from relatively simple elements in a computation- and memory-efficienct way.\n",
    "\n",
    "Let's try making references a level deeper by referencing `D`.  Note here we use the `<<` operator to add the references -- this is just shorthand, and is exactly equivalent to using `add_ref()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = Device()             # Create a new blank Device\n",
    "d_ref1 = X.add_ref(D)  # Reference the Device \"D\" that 3 references in it\n",
    "d_ref2 = X << D        # Use the \"<<\" operator to create a 2nd reference to D\n",
    "d_ref3 = X << D        # Use the \"<<\" operator to create a 2nd reference to D\n",
    "\n",
    "d_ref1.move([20,0])\n",
    "d_ref2.move([40,0])\n",
    "\n",
    "qp(X) # Quickplot the reference-containing device \"D\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Arrays of references\n",
    "\n",
    "Sometimes it's convenient to make an array or grid of the same geometry.  For that purpose, the GDSII spec allows you to define arrays of references.  In PHIDL, these are added with the `add_array()` function. Note that by GDSII definition these arrays are on a fixed grid -- PHIDL does however have more flexible arrangement options if desired, see for example `grid()` and `packer()`.\n",
    "\n",
    "Let's make a new device and put a big array of our Device `D` in it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "A = Device()           # Create a new blank Device\n",
    "d_ref1 = A.add_array(D, columns = 6, rows = 3, spacing = [20,15])  # Reference the Device \"D\" that 3 references in it\n",
    "\n",
    "qp(A) # Quickplot the reference-containing device \"D\""
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
